# -*- coding: utf-8 -*-
"""
Created on Mon Oct 14 16:58:31 2019

This script contains the constants needed by the pySICE library.

@author: bav@geus.dk
"""

import numpy as np

# solar spectrum constants
f0=32.38
f1=-160140.33
f2=7959.53
bet=   1./(85.34*1.e-3)
gam= 1./(401.79*1.e-3)

#ICE REFRATIVE INDEX
xa = np.array((2.010E-001,
2.019E-001,
2.100E-001,
2.500E-001,
3.00E-001,
3.500E-001,
3.900E-001,
4.000E-001,
4.100E-001,
4.200E-001,
4.300E-001,
4.400E-001,
4.500E-001,
4.600E-001,
4.700E-001,
4.800E-001,
4.900E-001,
5.000E-001,
5.100E-001,
5.200E-001,
5.300E-001,
5.400E-001,
5.500E-001,
5.600E-001,
5.700E-001,
5.800E-001,
5.900E-001,
6.000E-001,
6.100E-001,
6.200E-001,
6.300E-001,
6.400E-001,
6.500E-001,
6.600E-001,
6.700E-001,
6.800E-001,
6.900E-001,
7.000E-001,
7.100E-001,
7.200E-001,
7.300E-001,
7.400E-001,
7.500E-001,
7.600E-001,
7.700E-001,
7.800E-001,
7.900E-001,
8.000E-001,
8.100E-001,
8.200E-001,
8.300E-001,
8.400E-001,
8.500E-001,
8.600E-001,
8.700E-001,
8.800E-001,
8.900E-001,
9.000E-001,
9.100E-001,
9.200E-001,
9.300E-001,
9.400E-001,
9.500E-001,
9.600E-001,
9.700E-001,
9.800E-001,
9.900E-001,
1.000E+000,
1.010E+000,
1.020E+000,
1.030E+000,
1.040E+000,
1.050E+000,
1.060E+000,
1.070E+000,
1.080E+000,
1.090E+000,
1.100E+000,
1.110E+000,
1.120E+000,
1.130E+000,
1.140E+000,
1.150E+000,
1.160E+000,
1.170E+000,
1.180E+000,
1.190E+000,
1.200E+000,
1.210E+000,
1.220E+000,
1.230E+000,
1.240E+000,
1.250E+000,
1.260E+000,
1.270E+000,
1.280E+000,
1.290E+000,
1.300E+000,
1.310E+000,
1.320E+000,
1.330E+000,
1.340E+000,
1.350E+000,
1.360E+000,
1.370E+000,
1.380E+000,
1.390E+000,
1.400E+000,
1.410E+000,
1.420E+000,
1.430E+000,
1.440E+000,
1.449E+000,
1.460E+000,
1.471E+000,
1.481E+000,
1.493E+000,
1.504E+000,
1.515E+000,
1.527E+000,
1.538E+000,
1.563E+000,
1.587E+000,
1.613E+000,
1.650E+000,
1.680E+000,
1.700E+000,
1.730E+000,
1.760E+000,
1.800E+000,
1.830E+000,
1.840E+000,
1.850E+000,
1.855E+000,
1.860E+000,
1.870E+000,
1.890E+000,
1.905E+000,
1.923E+000,
1.942E+000,
1.961E+000,
1.980E+000,
2.000E+000,
2.020E+000,
2.041E+000,
2.062E+000,
2.083E+000,
2.105E+000,
2.130E+000,
2.150E+000,
2.170E+000,
2.190E+000,
2.220E+000,
2.240E+000,
2.245E+000,
2.250E+000,
2.260E+000,
2.270E+000,
2.290E+000,
2.310E+000,
2.330E+000,
2.350E+000,
2.370E+000,
2.390E+000,
2.410E+000,
2.430E+000,
2.460E+000,
2.500E+000))

ya = np.array((3.249E-011,
2.0E-011,
2.0E-011,
2.0E-011,
2.0E-011,
2.0E-011,
2.0E-011,
2.365E-011,
2.669E-011,
3.135E-011,
4.140E-011,
6.268E-011,
9.239E-011,
1.325E-010,
1.956E-010,
2.861E-010,
4.172E-010,
5.889E-010,
8.036E-010,
1.076E-009,
1.409E-009,
1.813E-009,
2.289E-009,
2.839E-009,
3.461E-009,
4.159E-009,
4.930E-009,
5.730E-009,
6.890E-009,
8.580E-009,
1.040E-008,
1.220E-008,
1.430E-008,
1.660E-008,
1.890E-008,
2.090E-008,
2.400E-008,
2.900E-008,
3.440E-008,
4.030E-008,
4.300E-008,
4.920E-008,
5.870E-008,
7.080E-008,
8.580E-008,
1.020E-007,
1.180E-007,
1.340E-007,
1.400E-007,
1.430E-007,
1.450E-007,
1.510E-007,
1.830E-007,
2.150E-007,
2.650E-007,
3.350E-007,
3.920E-007,
4.200E-007,
4.440E-007,
4.740E-007,
5.110E-007,
5.530E-007,
6.020E-007,
7.550E-007,
9.260E-007,
1.120E-006,
1.330E-006,
1.620E-006,
2.000E-006,
2.250E-006,
2.330E-006,
2.330E-006,
2.170E-006,
1.960E-006,
1.810E-006,
1.740E-006,
1.730E-006,
1.700E-006,
1.760E-006,
1.820E-006,
2.040E-006,
2.250E-006,
2.290E-006,
3.040E-006,
3.840E-006,
4.770E-006,
5.760E-006,
6.710E-006,
8.660E-006,
1.020E-005,
1.130E-005,
1.220E-005,
1.290E-005,
1.320E-005,
1.350E-005,
1.330E-005,
1.320E-005,
1.320E-005,
1.310E-005,
1.320E-005,
1.320E-005,
1.340E-005,
1.390E-005,
1.420E-005,
1.480E-005,
1.580E-005,
1.740E-005,
1.980E-005,
3.442E-005,
5.959E-005,
1.028E-004,
1.516E-004,
2.030E-004,
2.942E-004,
3.987E-004,
4.941E-004,
5.532E-004,
5.373E-004,
5.143E-004,
4.908E-004,
4.594E-004,
3.858E-004,
3.105E-004,
2.659E-004,
2.361E-004,
2.046E-004,
1.875E-004,
1.650E-004,
1.522E-004,
1.411E-004,
1.302E-004,
1.310E-004,
1.339E-004,
1.377E-004,
1.432E-004,
1.632E-004,
2.566E-004,
4.081E-004,
7.060E-004,
1.108E-003,
1.442E-003,
1.614E-003,
1.640E-003,
1.566E-003,
1.458E-003,
1.267E-003,
1.023E-003,
7.586E-004,
5.255E-004,
4.025E-004,
3.235E-004,
2.707E-004,
2.228E-004,
2.037E-004,
2.026E-004,
2.035E-004,
2.078E-004,
2.171E-004,
2.538E-004,
3.138E-004,
3.858E-004,
4.591E-004,
5.187E-004,
5.605E-004,
5.956E-004,
6.259E-004,
6.820E-004,
7.530E-004))


# OLCI channels
w = np.array((0.4000E+00,
0.4125E+00,
0.4425E+00,
0.4900E+00,
0.5100E+00,
0.5600E+00,
0.6200E+00,
0.6650E+00,
0.6737E+00,
0.6812E+00,
0.7088E+00,
0.7538E+00,
0.7613E+00,
0.7644E+00,
0.7675E+00,
0.7788E+00,
0.8650E+00,
0.8850E+00,
0.9000E+00,
0.9400E+00,
0.1020E+01))

# Imaginary part of ice refrative index at OLCI channels
bai = np.array((2.365E-11,
2.7E-11,
7.0E-11,
4.17E-10,
8.04E-10,
2.84E-09,
8.58E-09,
1.78E-08,
1.95E-08,
2.1E-08,
3.3E-08,
6.23E-08,
7.1E-08,
7.68E-08,
8.13E-08,
9.88E-08,
2.4E-07,
3.64E-07,
4.2E-07,
5.53e-07,
2.25E-06))
